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Department of Energy Office of Legacy Management Progress on Defense-Related Uranium Mines Program - 18119

The Defense-Related Uranium Mines (DRUM) Program provides the structure and basis for the US Department of Energy Office of Legacy Management (LM) to manage the verification and validation (V and V) of defense-related uranium mines (mines) that provided ore to the Atomic Energy Commission from 1947 to 1970. V and V activities are conducted to fully understand the scope of potential problems posed by these mines by determining their location, reclamation or remediation status, and potential impacts to public safety, human health, and the environment. Land management agencies have limited resources and have generally not conducted comprehensive inventories of abandoned uranium mines, thus adding to the need to undertake this program. LM has entered into memoranda of understanding (MOUs) with the US Bureau of Land Management (BLM) and US Forest Service (USFS) to facilitate a better understanding of the scope of the problem posed by these mines. Currently, LM has executed MOUs with the BLM state offices in Colorado, New Mexico, Utah, and Wyoming and the USFS Rocky Mountain Region, which includes the national forests in Colorado, Wyoming, and South Dakota. This collaborative effort with partner agencies has led LM to develop a V and V Work Plan that describes the numerous activities and types of data to be collected at the mines. V and V activities verify actual mine location, collect coordinates of mining-related features, collect radiological data and soil samples, identify potential physical safety hazards, prioritize mines using a risk-based screening approach, and report the information to partner agencies. The partner agencies may use the reports to assess priorities and determine if any further action is warranted. The DRUM Program goals are to: - Improve data quality and content in the LM national inventory of abandoned uranium mines; - Conduct site-specific reconnaissance at mines for data verification and validation; - Exchange mine information with other federal agencies and state governments to help address mines presenting the greatest risks; - Develop reports for each mine that will contain a risk scoring assessment to help each agency develop priorities. The preliminary risk screening methodology was based on a joint effort between LM and BLM to develop factors that would be based on field observations, field data, and laboratory data using a multiple-lines-of-evidence approach. The multiple-lines-of-evidence assessment allows land managers the opportunity and flexibility to query specific criteria and make rankings based on specific priorities. The risk screening for each mine is based on evaluating the primary hazards of physical safety and risks to human health and several modifying factors that include accessibility and ecological/environmental risks. Gamma radiation scans are performed across the disturbed area of the mine, and soil samples are taken from waste rock piles and drainages, when applicable. This paper presents the results of performing inventory, environmental sampling, and risk ranking along with other accomplishments and lessons learned during the initial year of V and V activities and reporting. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Activation of peroxisome proliferator-activated receptor-{alpha} enhances fatty acid oxidation in human adipocytes

Highlights: {yields} PPAR{alpha} activation increased mRNA expression levels of adipocyte differentiation marker genes and GPDH activity in human adipocytes. {yields} PPAR{alpha} activation also increased insulin-dependent glucose uptake in human adipocytes. {yields} PPAR{alpha} activation did not affect lipid accumulation in human adipocytes. {yields} PPAR{alpha} activation increased fatty acid oxidation through induction of fatty acid oxidation-related genes in human adipocytes. -- Abstract: Peroxisome proliferator-activated receptor-{alpha} (PPAR{alpha}) is a key regulator for maintaining whole-body energy balance. However, the physiological functions of PPAR{alpha} in adipocytes have been unclarified. We examined the functions of PPAR{alpha} using human multipotent adipose tissue-derived stem cells as a human adipocyte model. Activation of PPAR{alpha} by GW7647, a potent PPAR{alpha} agonist, increased the mRNA expression levels of adipocyte differentiation marker genes such as PPAR{gamma}, adipocyte-specific fatty acid-binding protein, and lipoprotein lipase and increased both GPDH activity and insulin-dependent glucose uptake level. The findings indicate that PPAR{alpha} activation stimulates adipocyte differentiation. However, lipid accumulation was not changed, which is usually observed when PPAR{gamma} is activated. On the other hand, PPAR{alpha} activation by GW7647 treatment induced the mRNA expression of fatty acid oxidation-related genes such as CPT-1B and AOX in a PPAR{alpha}-dependent manner. Moreover, PPAR{alpha} activation increased the production of CO{sub 2} and acid soluble metabolites, which are products of fatty acid oxidation, and increased oxygen consumption rate in human adipocytes. The data indicate that activation of PPAR{alpha} stimulates both adipocyte differentiation and fatty acid oxidation in human adipocytes, suggesting that PPAR{alpha} agonists could improve insulin resistance without lipid accumulation in adipocytes. The expected effects of PPAR{alpha} activation are very valuable for managing diabetic conditions accompanied by obesity, because PPAR{gamma} agonists, usually used as antidiabetic drugs, induce excessive lipid accumulation in adipocytes in addition to improvement of insulin resistance.

60 APPLIED LIFE SCIENCES↗

GBCGE Subsurface Database Explorer and APIs

This submission defines a DOI for the Great Basin Center for Geothermal Energy's (GBCGE) Subsurface Database Explorer web application and underlying data services, and acknowledges the INGENIOUS project as a major source of funding for data compilation and quality assurance. The GBCGE Subsurface Database Explorer is an interactive web mapping application that provides public access to the GBCGE Subsurface Database, and its collection of datasets pertinent to geothermal exploration, oil and gas exploration, critical mineral exploration, and other subsurface characterization for the Great Basin Region, western US. This is a living database, and will be continuously updated with new data and datasets as funding and motivations allow. The underlying database views that populate the web application are on an automated refresh schedule. Data sources and acknowledgements: We thank our partners with the Nevada Division of Minerals (NDOM), the Southern Methodist University (SMU), and Great Basin State Geological Surveys for their active efforts in data curation, schema design, and quality assurance. We also thank contributors among the USGS, Oregon Institute of Technology, State Divisions of Water Resources, State Divisions of Oil, Gas, and Minerals, and State Geological Surveys for open data availability and direct contributions made under the National Geothermal Data System (NGDS).

15 GEOTHERMAL ENERGY↗

Synergistic Challenges in Data-Intensive Science and Exascale Computing. Summary report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee, March 2013

The ASCAC Subcommittee on Synergistic Challenges in Data-Intensive Science and Exascale Computing has reviewed current practice and future plans in multiple science domains in the context of the challenges facing both Big Data and the Exascale Computing. challenges. The review drew from public presentations, workshop reports and expert testimony. Data-intensive research activities are increasing in all domains of science, and exascale computing is a key enabler of these activities. We briefly summarize below the key findings and recommendations from this report from the perspective of identifying investments that are most likely to positively impact both data-intensive science goals and exascale computing goals.

97 MATHEMATICS AND COMPUTING↗

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Cryogenic Refrigerator Applied to Freezing Test

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

Clean Cities Coalitions: 2022 Activity Report

The U.S. Department of Energy's (DOE's) Vehicle Technologies Office (VTO) works with local Clean Cities coalitions across the country as part of its Technology Integration Program. These efforts help businesses and consumers make smarter and more informed transportation energy choices that can save energy, lower costs, provide resilience through fuel diversification, and reduce emissions. This report summarizes the success and impact of coalition activities based on data and information provided in their annual reports.

33 ADVANCED PROPULSION SYSTEMS↗

Standardizing Activation Analysis: New Software for Photon Activation Analysis

Photon Activation Analysis (PAA) of environmental, archaeological and industrial samples requires extensive data analysis that is susceptible to error. For the purpose of saving time, manpower and minimizing error, a computer program was designed, built and implemented using SQL, Access 2007 and asp.net technology to automate this process. Based on the peak information of the spectrum and assisted by its PAA library, the program automatically identifies elements in the samples and calculates their concentrations and respective uncertainties. The software also could be operated in browser/server mode, which gives the possibility to use it anywhere the internet is accessible. By switching the nuclide library and the related formula behind, the new software can be easily expanded to neutron activation analysis (NAA), charged particle activation analysis (CPAA) or proton-induced X-ray emission (PIXE). Implementation of this would standardize the analysis of nuclear activation data. Results from this software were compared to standard PAA analysis with excellent agreement. With minimum input from the user, the software has proven to be fast, user-friendly and reliable.

07 ISOTOPE AND RADIATION SOURCES↗

Catalytic Activation of Esterases by PEGylation for Polyester Synthesis

Abstract In this work we explored PEGylation as an efficient strategy to improve esterase's catalytic performance. For this, we PEGylated three esterases, namely lipase from Candida antarctica B (CALB), lipase from Thermomyces lanuginosus (TL) and cutinase from Fusarium solani pisi (CUT) and evaluated their catalytic performance by using the biosynthesis of poly(ethylene glutarate) as model reaction. After PEGylation with a 5 kDa aldehyde‐PEG, CALB and cutinase revealed an increase of activity against p ‐nitrophenyl butyrate hydrolysis (2‐fold of increase for CALB and 4‐fold of increase for cutinase). Unmodified and PEGylated lipase TL displayed however similar activity results. The polymerase activity of native and PEGylated esterases was also assessed. The data revealed a higher polymerase activity for the lipase TL and cutinase PEGylated forms (88 % conversion for PEG‐lipase TL and 34 % for PEG‐cutinase). Molecular dynamics were used to evaluate the effect of PEG on the geometry of the active site of enzymes with lid domain (TL and CALB). These studies corroborate the experimental data revealing a more open active site cavity for the PEGylated catalysts facilitating the catalysis.

Noro, Jennifer↗

Anoxygenic phototroph of the Chloroflexota uses a type I reaction centre

Scientific exploration of phototrophic bacteria over nearly 200 years has revealed large phylogenetic gaps between known phototrophic groups that limit understanding of how phototrophy evolved and diversified. Here, through Boreal Shield lake water incubations, we cultivated an anoxygenic phototrophic bacterium from a previously unknown order within the Chloroflexota phylum that represents a highly novel transition form in the evolution of photosynthesis. Unlike all other known phototrophs, this bacterium uses a type I reaction centre (RCI) for light energy conversion yet belongs to the same bacterial phylum as organisms that use a type II reaction centre (RCII) for phototrophy. Using physiological, phylogenomic and environmental metatranscriptomic data, we demonstrate active RCI-utilizing metabolism by the strain alongside usage of chlorosomes and bacteriochlorophylls related to those of RCII-utilizing Chloroflexota members. Despite using different reaction centres, our phylogenomic data provide strong evidence that RCI-utilizing and RCII-utilizing Chloroflexia members inherited phototrophy from a most recent common phototrophic ancestor. The Chloroflexota phylum preserves an evolutionary record of the use of contrasting phototrophic modes among genetically related bacteria, giving new context for exploring the diversification of phototrophy on Earth.

59 BASIC BIOLOGICAL SCIENCES↗

Nonuniform cosmological birefringence and active galactic nuclei

The CMB constrains the cosmological-birefringence rotation angle to be |{alpha}| < or approx. 1 deg. (1{sigma}) out to redshifts z{approx_equal}1100 for a rotation that is uniform across the sky. However, the rotation angle {alpha}({theta},{phi}) may vary with position ({theta},{phi}) on the sky, and if so, then it can be sought in current and future active galactic nuclei data. An upper limit <{alpha}{sup 2}>{sup 1/2} < or approx. 3.7 deg. to the scatter in the position-angle-polarization offsets in a sample of only N=9 active galactic nuclei already constrains the rotation spherical-harmonic coefficients to (4{pi}){sup -1/2{alpha}}{sub lm} < or approx. 3.7 deg. and constrains the power spectrum for {alpha} in models where it is a stochastic field. Future constraints can be improved with more sources and by analyzing well-mapped sources with a tensor-harmonic decomposition of the polarization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

WETO Stack [SWR-24-81]

The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project’s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy’s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.

Mudafort, Rafael↗

Revealing Physical Activity of GRB Central Engine with Macronova/Kilonova Data

The modeling of Li-Paczyński macronova/kilonova signals gives a reasonable estimate on the neutron-rich material ejected during the neutron star mergers. Usually the accretion disk is more massive than the macronova ejecta, with which the efficiencies of converting the disk mass into prompt emission of three merger-driven GRBs can hence be directly constrained. Supposing the macronovae/kilonovae associated with GRB 050709, GRB 060614, and GRB 130603B arose from radioactive decay of the r -process material, the upper limit on energy conversion efficiencies are found to be as low as ∼10{sup −6}–10{sup −4}. Moreover, for all three events, neutrino annihilation is likely powerful enough to account for the brief gamma-ray flashes. Neutrino annihilation can also explain the “extended” emission lasting ∼100 s in GRB 050709, but does not work for the one in GRB 060614. These progresses demonstrate that the macronova can serve as a novel probe of the central engine activity.

79 ASTRONOMY AND ASTROPHYSICS↗

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗

Structure of the activated Edc1-Dcp1-Dcp2-Edc3 mRNA decapping complex with substrate analog poised for catalysis

The conserved decapping enzyme Dcp2 recognizes and removes the 5' eukaryotic cap from mRNA transcripts in a critical step of many cellular RNA decay pathways. Dcp2 is a dynamic enzyme that functions in concert with the essential activator Dcp1 and a diverse set of coactivators to selectively and efficiently decap target mRNAs in the cell. Here we present a 2.84 Å crystal structure of K . lactis Dcp1–Dcp2 in complex with coactivators Edc1 and Edc3, and with substrate analog bound to the Dcp2 active site. Our structure shows how Dcp2 recognizes cap substrate in the catalytically active conformation of the enzyme, and how coactivator Edc1 forms a three-way interface that bridges the domains of Dcp2 to consolidate the active conformation. Kinetic data reveal Dcp2 has selectivity for the first transcribed nucleotide during the catalytic step. The heterotetrameric Edc1–Dcp1–Dcp2–Edc3 structure shows how coactivators Edc1 and Edc3 can act simultaneously to activate decapping catalysis.

Science & Technology - Other Topics↗

United States Department of Energy severe accident research following the Fukushima Daiichi accidents

The U.S. Department of Energy (DOE) has played a major role in the U.S. response to the events at Fukushima Daiichi. During the first several weeks following the accident, U.S. assistance efforts were guided by results from a significant and diverse set of analyses. In the months that followed, a coordinated analysis activity aimed at gaining a more thorough understanding of the accident sequence was completed using laboratory-developed, system-level best-estimate accident analysis codes, while a parallel analysis was conducted by U.S. industry. A comparison of predictions for Unit 1 from these two studies indicated significant differences between MAAP and MELCOR results for key plant parameters, such as in-core hydrogen production. On that basis, a crosswalk was completed to determine the key modeling variations that led to these differences. In parallel with these activities, it became clear that there was a need to perform a technology gap evaluation on accident-tolerant components and severe accident analysis methodologies with the goal of identifying any data and/or knowledge gaps that may exist given the current state of light water reactor (LWR) severe accident research and augmented by insights from Fukushima. In addition, there is growing international recognition that data from Fukushima could significantly reduce uncertainties related to severe accident progression, particularly for boiling water reactors. On these bases, a group of U. S. experts in LWR safety and plant operations was convened by the DOE Office of Nuclear Energy (DOE-NE) to complete technology gap analysis and Fukushima forensics data needs identification activities. The results from these activities were used as the basis for refining DOE-NE's severe accident research and development (R&D) plan. Finally, this paper provides a high-level review of DOE-sponsored R&D efforts in these areas, including planned activities on accident-tolerant components and accident analysis methods.

61 RADIATION PROTECTION AND DOSIMETRY↗

Active workflow system for near real-time extreme-scale science. In: PPAA '14 Proceedings of the first workshop on Parallel programming for analytics applications

In recent years, streaming-based data processing has been gaining substantial traction for dealing with overwhelming data generated by real-time applications, from both enterprise sources and scientific computing. In this work, however, we look at an emerging class of scientific data with Near Real-Time (NRT) requirement, in which data is typically generated in a bursty fashion with the near real-time constraints being applied primarily between bursts, rather than within a stream. A key challenge for this types of data sources is that the processing time per data element is not uniform, and not always feasible to predict. Given the observations on the increasing unpredictability of compute load and system dynamics, this work looks to adapt streaming-based approach to the context of this new class of large experiments and simulations that have complex run-time control and analysis issues. In particular, we deploy a novel two-tier scheme for handling the increasing unpredictability of runtime behaviors: Instead of relying on determining what and where to run the scientific workflows beforehand or partial dynamically, the decision will also be adaptively enhanced online according to system runtime status. This is enabled by embedding workflow along with data streams. Specifically, we break data outputs generated from experiments or simulations into multiple self-describing "chunks", which we call active data objects. As such, if there is a transient hotspot observed, a data object with unfinished workflow pipeline can break its previous schedule and search for a least loaded location to continue the execution. Our preliminary experiment results based on synthetic workloads demonstrate the proposed active workflow system as a very promising solution by outperforming the state-of-the-art semi-dynamic workflow schedulers with an improved workflow completion time, as well as a good scalability.

Zhang, Yanwei↗

An Active Learning-Based Streaming Pipeline for Reduced Data Training of Structure Finding Models in Neutron Diffractometry

Structure determination workloads in neutron diffractometry are computationally expensive and routinely require several hours to many days to determine the structure of a material from its neutron diffraction patterns. The potential for machine learning models trained on simulated neutron scattering patterns to significantly speed up these tasks have been reported recently. However, the amount of simulated data needed to train these models grows exponentially with the number of structural parameters to be predicted and poses a significant computational challenge. To overcome this challenge, we introduce a novel batch-mode active learning (AL) policy that uses uncertainty sampling to simulate training data drawn from a probability distribution that prefers labelled examples about which the model is least certain. We confirm its efficacy in training the same models with ∼ 75% less training data while improving the accuracy. We then discuss the design of an efficient stream-based training workflow that uses this AL policy and present a performance study on two heterogeneous platforms to demonstrate that, compared with a conventional training workflow, the streaming workflow delivers ∼ 20% shorter training time without any loss of accuracy.

Wang, Tianle [Brookhaven National Laboratory (BNL)↗

Radiation-Induced Survivin Nuclear Accumulation is Linked to DNA Damage Repair

Purpose: Increased expression of survivin has been identified as a negative prognostic marker in a variety of human cancers. We have previously shown that survivin is a radiation-resistance factor and that the therapeutic effect of survivin knock-down might result from an impaired DNA repair capacity. In this study, we aimed to elucidate an interrelationship between survivin's cellular localization and DNA double-strand break repair. Methods and Materials: Survivin's cellular distribution and nuclear complex formation were assayed by Western blotting of subcellular fractions, by immunofluorescence staining, and co-immunoprecipitation in SW480 colorectal cancer cells. DNA repair capacity was analyzed by kinetics of gamma-H2AX foci formation, and by DNA-dependent protein kinase (DNA-PKcs) assays in the presence of survivin-specific or nonspecific control siRNA. Results: Following irradiation, we observed a rapid nuclear accumulation of survivin and subsequent phosphorylation of the protein in the nucleus. Co-immunoprecipitation analyses from nuclear extracts revealed an interaction among survivin, Ku70, gamma-H2AX, MDC1, and DNA-PKcs that was confirmed by immunofluorescence co-localization in nuclear foci. Survivin knock down by siRNA resulted in an impaired DNA double strand break repair, as demonstrated by an increased detection of gamma-H2AX foci/nucleus at 60 min and a higher amount of residual gamma-H2AX foci at 24 hr postirradiation. Furthermore, we detected in survivin-depleted cells a hampered S2056 autophosphorylation of DNA-PKcs and a significantly decreased DNA-PKcs kinase activity. Conclusion: These data indicate that nuclear survivin is linked to DNA double-strand break repair by interaction with members of the DNA double-strand breaks repair machinery, thus regulating DNA-PKcs activity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗